ArticleInvestigative ophthalmology & visual science2021
Differential Tissue Metabolic Signatures in IgG4-Related Ophthalmic Disease and Orbital Mucosa-Associated Lymphoid Tissue Lymphoma.
Article in Investigative ophthalmology & visual science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 20 citations in OpenAlex.
- Application of artificial intelligence in differentiating IgG4-related ophthalmic disease and orbital MALT lymphoma: a review of radiomics and deep learning advances.Frontiers in immunology · 2026Review
- UPLC-MS/MS-based metabolomics analysis identifies disease-associated metabolic signatures of B cells from patients with IgG4-RD.Frontiers in immunology · 2026Article
- Gene expression cluster differences and molecular correlation with the STING pathway in orbital MALT lymphoma and orbital IgG4-related eye disease.Discover oncology · 2025Article
- Omics in IgG4-related disease.Chinese medical journal · 2025Review
- Perilesional dominance: radiomics of multiparametric MRI enhances differentiation of IgG4-Related ophthalmic disease and orbital MALT lymphoma.BMC medical imaging · 2025Article
- Characteristics of orbital lymphoproliferative disorders: a retrospective study of 84 cases.Eye (London, England) · 2025Article
- The significance of PET/CT combined with machine learning models for the classification of lymphoma involvement and metastases in enlarged lymph nodes.Frontiers in oncology · 2025Article
- Comparison of volumetric responses to different corticosteroid administration methods in IgG4-related ophthalmic disease.PloS one · 2025Article
- Artificial intelligence-based differential diagnosis of orbital MALT lymphoma and IgG4 related ophthalmic disease using hematoxylin-eosin images.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2024Article
- Salivary metabolomic biomarkers for esophageal and gastric cancers by liquid chromatography-mass spectrometry.Cancer science · 2024Article
- Radiomics analysis of T1WI and T2WI magnetic resonance images to differentiate between IgG4-related ophthalmic disease and orbital MALT lymphoma.BMC ophthalmology · 2023Article
- Machine Learning-Based Integration of Metabolomics Characterisation Predicts Progression of Myopic Retinopathy in Children and Adolescents.Metabolites · 2023Article
- Application of response surface methodology (RSM) for optimization of the supercritical COFood chemistry: X · 2022Article
- Metabolic Reprogramming in Hematologic Malignancies: Advances and Clinical Perspectives.Cancer research · 2022Review
- Evaluation of Orbital Lymphoproliferative and Inflammatory Disorders by Gene Expression Analysis.International journal of molecular sciences · 2022Article
- Upregulated Expression of Activation-Induced Cytidine Deaminase in Ocular Adnexal Marginal Zone Lymphoma with IgG4-Positive Cells.International journal of molecular sciences · 2021Article
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12 authors at 1 institution in 1 country.
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Abstract
Purpose: To identify tissue metabolomic profiles in biopsy specimens with IgG4-related ophthalmic disease (IgG4-ROD) and mucosa-associated lymphoid tissue (MALT) lymphoma and investigate their potential implication in the disease pathogenesis and biomarkers. Methods: We conducted a comprehensive analysis of the metabolomes and lipidomes of biopsy-proven IgG4-ROD (n = 22) and orbital MALT lymphoma (n = 21) specimens and matched adjacent microscopically normal adipose tissues using liquid chromatography time-of-flight mass spectrometry. The altered metabolomic profiles were visualized by heat map and principal component analysis. Metabolic pathway analysis was performed by Metabo Analyst 4.0 using differentially expressed metabolites. The diagnostic performance of the metabolic markers was evaluated using receiver operating characteristic curves. Machine learning algorithms were implemented by random forest using the R environment. Finally, an independent set of 18 IgG4-ROD and 17 orbital MALT lymphoma specimens were used to validate the identified biomarkers. Results: The principal component analysis showed a significant difference of both IgG4-ROD and orbital MALT lymphoma for biopsy specimens and controls. Interestingly, lesions in IgG4-ROD were uniquely enriched in arachidonic metabolism, whereas those in orbital MALT lymphoma were enriched in tricarboxylic acid cycle metabolism. We identified spermine as the best discriminator between IgG4-ROD and orbital MALT lymphoma, and the area under the receiver operating characteristic curve of the spermine to discriminate between the two diseases was 0.89 (95% confidence interval, 0.803-0.984). A random forest model incorporating a panel of five metabolites showed a high area under the receiver operating characteristic curve value of 0.983 (95% confidence interval, 0.981-0.984). The results of validation revealed that four tissue metabolites: N1,N12-diacetylspermine, spermine, malate, and glycolate, had statistically significant differences between IgG4-ROD and orbital MALT lymphoma with receiver operating characteristic values from 0.708 to 0.863. Conclusions: These data revealed the characteristic differences in metabolomic profiles between IgG4-ROD and orbital MALT lymphoma, which may be useful for developing new diagnostic biomarkers and elucidating the pathogenic mechanisms of these common orbital lymphoproliferative disorders.
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